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Initial commit of the mesh navigation tutorials: three synthetic worl…
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…ds and one robot.

Co-authored-by: Matthias Holoch <[email protected]>
Co-authored-by: Justus Braun <[email protected]>
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15 changes: 15 additions & 0 deletions .github/workflows/humble.yaml
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name: Humble CI - Build and Test

on:
push:
branches:
- 'humble'
pull_request:
workflow_dispatch:
branches:
- '*'

jobs:
build_and_test:
uses: naturerobots/github_automation_public/.github/workflows/humble_ci.yaml@main
secrets: inherit
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83 changes: 72 additions & 11 deletions README.md
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# Mesh Navigation Tutorials
Placeholder repository for a potential [ROSCon 2024](https://roscon.ros.org/2024/) talk.
<div align="center">
<h1>
Mesh Navigation Tutorials
</h1>
</div>

Here, we will release tutorials that provide entrypoints for new users interested in 3D navigation on meshes.
Besides documentation, it includes a range of real-world and artificial environments that are ready to use: Complete with simulation, launch files, and configuration files.
<div align="center">
<a href="https://github.com/naturerobots/mesh_navigation">Mesh Navigation</a>
<span>&nbsp;&nbsp;&nbsp;&nbsp;</span>
<a href="https://github.com/naturerobots/mesh_navigation_tutorials/wiki">Documentation</a>
<span>&nbsp;&nbsp;&nbsp;&nbsp;</span>
<a href="https://www.youtube.com/@nature-robots">Videos</a>
<span>&nbsp;&nbsp;&nbsp;&nbsp;</span>
<a href="https://github.com/naturerobots/mesh_navigation_tutorials/issues">Issues</a>
<br />
</div>

![Mesh Navigation on simple tray dataset](docs/images/mesh_nav_on_tray.png "Mesh Navigation on simple tray dataset")

![Mesh Navigation on real world dataset: Botanical garden Osnabrück](docs/images/mesh_nav_on_botanical_garden.png "Mesh Navigation on real world dataset: Botanical garden Osnabrück")
<br/>

# Related Repositories
- [Move Base Flex](https://github.com/magazino/move_base_flex) ([IROS 2018 paper](https://doi.org/10.1109/IROS.2018.8593829))
- [Mesh Tools](https://github.com/naturerobots/mesh_tools) ([RAS 2021 paper](https://doi.org/10.1016/j.robot.2020.103688))
This repository contains a set of examples to quickly and easily start with [mesh_navigation](https://github.com/naturerobots/mesh_navigation).
We provide different scenarios where our approach excels over state-of-the art 2D or 2.5D approaches.
We will explain different parameter sets in more detail and show how to fine-tune [mesh_navigation](https://github.com/naturerobots/mesh_navigation) in various scenarios.
Our example worlds consists of both real-world and hand-modelled scenarios.
With the hand-modelled examples we particularly aim to support low-end computers or laptops.


*Note*: Because of an great interest of people we talked to, we decided to release this repository in an unfinished state. It is still under construction and will be extended by more synthetic and real-world recorded worlds and detailed docs. It's open-source: Feel free to contribute.

## Requirements and Installation

* A working ROS 2 installation (we target `humble` at the moment).
* The tutorial's ROS 2 dependencies
* Clone source dependencies: Run `vcs import --input mesh_navigation_tutorials/source_dependencies.yaml` in your ROS 2 workspace source directory.
* Get packaged dependencies: Run `rosdep install --from-paths . --ignore-src -r -y` from within your ROS 2 workspace source directory.
* Build via `colcon build --packages-up-to mesh_navigation_tutorials`, from within your ROS 2 workspace root directory.

## Run the Examples

### Launch
```console
ros2 launch mesh_navigation_tutorials mesh_navigation_tutorial_launch.py world_name:=floor_is_lava
```

You change `floor_is_lava` by any world name that is available with this repository (see all by calling launch file with `--show-args`). Those are:

| Name | World | Default Map | Description |
|------|-------|-----|-------------|
| tray | ![tray_world](.resources/tray_world.png) | ![tray_map](.resources/tray_map.png)| This world is a rectangular area with a wall around the perimeter. |
| floor_is_lava | ![floor_is_lava_world](.resources/floor_is_lava_world.png) | ![floor_is_lava_map](.resources/floor_is_lava_map.png)| This world contains a square area with with two pits and a connecting section at a slightly higher elevation.
| parking_garage | ![parking_garage_world](.resources/parking_garage_world.png) | ![parking_garage_map](.resources/parking_garage_map.png)| This world represents a parking garage with multiple floors connected by ramps. |

When running a simulated world, you can save some resources by not running the gazebo GUI: Add the `start_gazebo_gui:=False` launch argument.

### Rviz GUI
In rviz, you should be able to see the mesh map.
This map is being used for navigation.

In order to make the robot move, find the "Mesh Goal" tool at the top.
With it, you can click on any part of the mesh.
Click and hold to set a goal pose.
The MbfGoalActions rviz plugin contains a very tiny state machine that performs the following actions:
* subscribe to that goal pose
* get a path to that pose
* execute that path

## Detailed Instructions

For more detailed instructions on how to parameterize things or what things can be changed see the [wiki](https://github.com/naturerobots/mesh_navigation_tutorials/wiki)


## Related Repositories
- [Move Base Flex](https://github.com/magazino/move_base_flex) ([IROS 2018](https://doi.org/10.1109/IROS.2018.8593829))
- [Mesh Tools](https://github.com/naturerobots/mesh_tools) ([RAS 2021](https://doi.org/10.1016/j.robot.2020.103688))
- [Mesh Navigation](https://github.com/naturerobots/mesh_navigation) ([ICRA 2021 paper for Continuous Vector Field Planner, CVP](https://doi.org/10.1109/ICRA48506.2021.9560981))
- [MICP-L](https://github.com/uos/rmcl) ([paper on arxiv](https://arxiv.org/abs/2210.13904))
- [Rmagine](https://github.com/uos/rmagine) ([ICRA 2023 paper](https://doi.org/10.1109/ICRA48891.2023.10161388))
- [Rmagine](https://github.com/uos/rmagine) ([ICRA 2023](https://doi.org/10.1109/ICRA48891.2023.10161388))
- [MICP-L](https://github.com/uos/rmcl) ([IROS 2024](https://arxiv.org/abs/2210.13904))
- [RMCL](https://github.com/uos/rmcl)
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22 changes: 22 additions & 0 deletions mesh_navigation_tutorials/CMakeLists.txt
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cmake_minimum_required(VERSION 3.8)
project(mesh_navigation_tutorials)

if(CMAKE_COMPILER_IS_GNUCXX OR CMAKE_CXX_COMPILER_ID MATCHES "Clang")
add_compile_options(-Wall -Wextra -Wpedantic -Werror)
endif()

# find dependencies
find_package(ament_cmake REQUIRED)

# install
install(DIRECTORY config launch rviz maps
DESTINATION share/${PROJECT_NAME}
)

# test
if(BUILD_TESTING)
find_package(ament_lint_auto REQUIRED)
ament_lint_auto_find_test_dependencies()
endif()

ament_package()
81 changes: 81 additions & 0 deletions mesh_navigation_tutorials/config/ekf.yaml
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ekf_filter_node:
ros__parameters:
frequency: 50.0
two_d_mode: true

debug: false

map_frame: map # Defaults to "map" if unspecified
odom_frame: odom # Defaults to "odom" if unspecified
base_link_frame: base_footprint # Defaults to "base_link" if unspecified
world_frame: odom # Defaults to the value of odom_frame if unspecified

odom0: /odom
odom0_config: [false, false, false, #xyz
false, false, false, # rpy
true, false, false, #vxyz
false, false, true, #vrpy
false, false, false] #axyz

odom0_differential: false
# odom0_relative: true

imu0: /imu/data
imu0_config: [false, false, false, #xyz
false, false, false, # rpy
false, false, false, #vxyz
true, true, true, #vrpy
false, false, false] #axyz
imu0_differential: false

use_control: false

# Whether the input (assumed to be cmd_vel) is a geometry_msgs/Twist or geometry_msgs/TwistStamped message. Defaults to
# false.
stamped_control: true

# The last issued control command will be used in prediction for this period. Defaults to 0.2.
control_timeout: 0.2

# Which velocities are being controlled. Order is vx, vy, vz, vroll, vpitch, vyaw.
control_config: [true, false, false, false, false, true]

# Places limits on how large the acceleration term will be. Should match your robot's kinematics.
acceleration_limits: [1.3, 0.0, 0.0, 0.0, 0.0, 3.4]

# Acceleration and deceleration limits are not always the same for robots.
deceleration_limits: [1.3, 0.0, 0.0, 0.0, 0.0, 4.5]

# If your robot cannot instantaneously reach its acceleration limit, the permitted change can be controlled with these
# gains
acceleration_gains: [0.8, 0.0, 0.0, 0.0, 0.0, 0.9]

# If your robot cannot instantaneously reach its deceleration limit, the permitted change can be controlled with these
# gains
deceleration_gains: [1.0, 0.0, 0.0, 0.0, 0.0, 1.0]
# imu0_relative: true

# imu0_remove_gravitational_acceleration: true

# process_noise_covariance: [0.01, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
# 0.0, 0.01, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
# 0.0, 0.0, 0.2, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
# 0.0, 0.0, 0.0, 0.01, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
# 0.0, 0.0, 0.0, 0.0, 0.01, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
# 0.0, 0.0, 0.0, 0.0, 0.0, 0.01, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
# 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.025, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
# 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.025, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
# 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.1, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
# 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.01, 0.0, 0.0, 0.0, 0.0, 0.0,
# 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.01, 0.0, 0.0, 0.0, 0.0,
# 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.01, 0.0, 0.0, 0.0,
# 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.1, 0.0, 0.0,
# 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.1, 0.0,
# 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.1]

# [ADVANCED] This represents the initial value for the state estimate error covariance matrix. Setting a diagonal
# value (variance) to a large value will result in rapid convergence for initial measurements of the variable in
# question. Users should take care not to use large values for variables that will not be measured directly. The values
# are ordered as x, y, z, roll, pitch, yaw, vx, vy, vz, vroll, vpitch, vyaw, ax, ay, az. Defaults to the diagonal values below
# if unspecified. In this example, we specify only the diagonal of the matrix.
# initial_estimate_covariance: [1e-9, 1e-9, 1e-9, 1e-9, 1e-9, 1e-9, 1e-9, 1e-9, 1e-9, 1e-9, 1e-9, 1e-9, 1e-9, 1e-9, 1e-9]
60 changes: 60 additions & 0 deletions mesh_navigation_tutorials/config/mbf_mesh_nav.yaml
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move_base_flex:
ros__parameters:
global_frame: 'map'
robot_frame: 'base_footprint'
odom_topic: 'odom'

use_sim_time: true
force_stop_at_goal: true
force_stop_on_cancel: true

planners: ['mesh_planner']
mesh_planner:
type: 'cvp_mesh_planner/CVPMeshPlanner'
cost_limit: 0.8
publish_vector_field: true
planner_patience: 10.0
planner_max_retries: 2
project_path_onto_mesh: false

controllers: ['mesh_controller']
mesh_controller:
type: 'mesh_controller/MeshController'
ang_vel_factor: 7.0
lin_vel_factor: 1.0

controller_patience: 2.0
controller_max_retries: 4
dist_tolerance: 0.2
angle_tolerance: 0.8
cmd_vel_ignored_tolerance: 10.0

mesh_map:
mesh_part: 'mesh'

layers: ['border', 'height_diff', 'roughness', 'inflation']

height_diff:
type: 'mesh_layers/HeightDiffLayer'
factor: 1.0
threshold: 0.8

border:
type: 'mesh_layers/BorderLayer'
factor: 1.0
border_cost: 1.0
threshold: 0.2

roughness:
type: 'mesh_layers/RoughnessLayer'
factor: 1.0
threshold: 0.8

inflation:
type: 'mesh_layers/InflationLayer'
factor: 1.0
inflation_radius: 0.4
inscribed_radius: 0.2
lethal_value: 1.0
inscribed_value: 0.8
repulsive_field: false
44 changes: 44 additions & 0 deletions mesh_navigation_tutorials/config/rmcl_micpl.yaml
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micp_localization:
ros__parameters:

# required
base_frame: base_footprint
map_frame: map
odom_frame: odom

# rate of broadcasting tf transformations
tf_rate: 50.0

micp:
# merging on gpu or cpu
combining_unit: cpu
# maximum number of correction steps per second
# lower this to decrease the correction speed but save energy
corr_rate_max: 20.0

# adjust max distance dependend of the state of localization
adaptive_max_dist: True # enable adaptive max dist

# DEBUGGING
# corr = correspondences
viz_corr: True
# corr = correction
print_corr_rate: False
disable_corr: False

# initial pose changes
trans: [0.0, 0.0, 0.0]
rot: [0.0, 0.0, 0.0] # euler angles (3) or quaternion (4)

# describe your sensor setup here
sensors: # list of range sensors - at least one is required
laser3d:
topic: cloud
topic_type: sensor_msgs/msg/PointCloud2
# normally it could also be a more memory-friendly spherical sensor model.
# However, I dont trust the Gazebo sensor
type: o1dn
model:
range_min: 0.5
range_max: 130.0
orig: [0.0, 0.0, 0.0]
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import os

from ament_index_python.packages import get_package_share_directory

from launch import LaunchDescription
from launch.actions import DeclareLaunchArgument
from launch.substitutions import LaunchConfiguration

from launch_ros.actions import Node

def generate_launch_description():
launch_args = [
DeclareLaunchArgument("mesh_map_path",
description='Path to the mesh file that defines the map.',
),
]
mesh_map_path = LaunchConfiguration('mesh_map_path')

mbf_mesh_nav_config = os.path.join(
get_package_share_directory('mesh_navigation_tutorials'),
'config',
'mbf_mesh_nav.yaml'
)

mesh_nav_server = Node(
name='move_base_flex',
package='mbf_mesh_nav',
executable='mbf_mesh_nav',
remappings=[
('/move_base_flex/cmd_vel', '/cmd_vel'),
],
parameters=[
mbf_mesh_nav_config,
{'mesh_map.mesh_file': mesh_map_path},
],
)

return LaunchDescription(
launch_args + [
mesh_nav_server,
])
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